We recently presented our project on Real-time data monitoring System with Nanorobotics at 2021 Undergraduate Research Conference.
Natural disasters and technical failures are destroying thousands of buildings every year as per the statistics of 2020. Therefore, our team is approaching to effectively build a nano-robot, which minimizes the financial loss by monitoring the real-time situations of the affected area, therefore, suggesting a better response. A real-time monitoring application helps to sense and transmit the data to our main Graphical User Interface (GUI).
Starting today, Dr. Ma joins the Editorial Board of IEEE Transactions on Vehicular Technology as an Associate Editor serving the area of Vehicular Electronics and Systems. IEEE Transactions on Vehicular Technology is dedicated to the publication of peer-reviewed original contributions of research regarding the theory and practice of electrical and electronics technology in vehicles and vehicular systems. More information about the transaction can be found here.
Utilizing the predictive traffic information, automated vehicle can achieve efficient motion planning and control to significantly reduce its fuel consumption, often noted as “eco-driving” strategy in literatures. The impacts of such a strategy on mixed traffic where human driven vehicles and automated vehicles share the road, however, is unclear due to human drivers’ diverse driving behaviors when interacting with automated vehicles in real world. In our latest work Energetic Impacts Evaluation of Eco-Driving on Mixed Traffic with Driver Behavioral Diversity (accepted by the IEEE Transactions on Intelligent Transportation Systems) we try to answer this question through a data-driven modeling approach.
Ph.D. student Mehmet Ozkan at MALab presented our recent work entitled Inverse Reinforcement Learning Based Driver Behavior Analysis and Fuel Economy Assessment during the 2020 ASME Dynamic Systems and Control Conference.
First year Ph.D. student Mehmet Ozkan at MALab has recent work entitled Eco-Driving of Connected and Automated Vehicle with Preceding Driver Behavior Prediction accepted by the ASME Journal of Dynamic Systems, Measurement and Control. Congratulations!
First year Ph.D. student Mehmet Ozkan at MALab presented our recent work entitled A Predictive Control Design with Speed Previewing Information for Vehicle Fuel Efficiency Improvement during the 2020 American Control Conference. This marks the first student paper from MALab since established in August, 2019.
Our recent proposal has been funded by Alternate Energy Research Initiative from College of Engineering. This project focuses on improving the energy efficiency and reducing emissions of the automotive and transportation systems through modeling, control, and optimization of ground vehicles powered by traditional fossil fuel, battery, and combinations of other alternative energy sources.
First year Ph.D. student Mehmet Ozkan at MALab has been accepted into Leadership And Mentorship Program (LAMP), Community of Scholars at Texas Tech University. This $600 scholarship from Dean of the Whitacre College of Engineering aims to support graduate student to practice the skills of teaching and instructing individual students.
Mehmet joined MALab in August, 2019. His research includes Connected and Autonomous Vehicle and Drivers Modelling and Analysis.